Nature-based solutions to address anxiety disorders: A cross-sectional ecological study of green spatial patterns in Taiwan

Air pollution and heat increase the prevalence and risk of anxiety disorders, which are particularly severe under the increasing trends of climate change and urbanization. Well-designed green spaces have mediating effects on the threats posed by environmental deterioration and promote public health. However, previous research has overlooked these effects. This cross-sectional ecological study applied partial least squares structural equation modeling to data from Taiwanese cities and towns to infer the vital influences of and complex relationships among green spatial patterns (i.e., the dispersion, patch area, fragmentation, aggregation, and coverage ratio of green spaces), socioeconomic status (i.e., income and population aging), atmospheric environment (i.e., air pollution and high temperature), and anxiety disorders. The results reveal that minimizing the dispersion of green spaces and maximizing their patch area and coverage ratio are associated with reduced prevalence of anxiety disorders. Air pollution and high temperature mediate the influence of green spatial patterns on anxiety disorders. Population aging, air pollution, and high temperature are factors that increase the prevalence rate of anxiety disorders, whereas income level has a negative effect. This study identified the pathways and influences (i.e., indirect, direct, and total impacts) of green spatial pattern characteristics on anxiety disorders. These findings show that the adoption of effective greening policies may promote the development of healthy cities. Moreover, this study provides a useful methodology for clarifying complex pathways and identifying vital factors that can be applied to future research in health science and policy.